deploy-collection

Deploy the full Content Agents package with a provider-neutral, endpoint-driven, multi-instance strategy. Use when the user asks to deploy all content agents, deploy material/physics/texture together, configure shared OVRTX rendering, choose VLM/LLM/image-gen/embedding endpoints, test the full package, or use Brev as an optional self-hosted dependency provider.

설치로 이동

저장소: NVIDIA-Omniverse/usd-content-agents
최근 소스 활동: 2026년 7월 21일 16:24
감지된 SKILL.md 언어: 영어
스타: 188
포크: 23

설치 방법

기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.

npx skills add https://github.com/NVIDIA-Omniverse/usd-content-agents --skill deploy-collection

명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.

로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.

소스 파일 검토

설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.

파일 탐색기

6 개 파일

SKILL.md

소스 지침 · 읽기 전용 미리보기

검색으로 돌아가기 설치로 돌아가기

material-agent-cli

Run the direct Material Agent CLI for config-driven VLM material assignment pipelines. Use when the user wants to run material-agent commands directly, edit or execute a material-agent config YAML, resume a fixed pipeline, benchmark material predictions, build datasets from USD files, apply predicted materials, configure a material run, or try a SimReady demo.

2026-07-30

deploy-physics-agent-docker

Deploy the physics-agent-service locally using Docker Compose with the bundled OVRTX GPU rendering sidecar. Use when user wants to run physics agent with docker, docker compose, set up local deployment of the physics service, run it on a GPU box, start physics agent containers, configure the VLM provider for physics docker deployment, or check whether tune/refine service routes are usable. Trigger phrases include "deploy physics agent", "docker compose physics", "run physics agent locally", "start physics service docker", "physics compose up", "physics agent docker".

2026-07-30

vision

Analyze images using a Vision-Language Model through the wu CLI. Use when the user wants to describe an image, caption a picture, ask questions about visual content, inspect renders or screenshots, compare visual evidence, or produce text or JSON answers with public VLM backends.

2026-07-30

이 저장소의 모든 Skills 보기

./deploy/collection/deploy.py plan

./deploy/collection/deploy.py up

./deploy/collection/deploy.py status
./deploy/collection/deploy.py smoke

source .venv/bin/activate
python -m py_compile deploy/collection/deploy.py
./deploy/collection/deploy.py plan
./deploy/collection/deploy.py render-env
docker compose --env-file deploy/collection/.collection.generated.env \
  -f deploy/collection/docker-compose.agents.yml config --quiet

name	deploy-collection
description	Deploy the full Content Agents package with a provider-neutral, endpoint-driven, multi-instance strategy. Use when the user asks to deploy all content agents, deploy material/physics/texture together, configure shared OVRTX rendering, choose VLM/LLM/image-gen/embedding endpoints, test the full package, or use Brev as an optional self-hosted dependency provider.
version	0.1.0
author	NVIDIA Content Agents
tags	["content-agents","collection","deployment","brev"]
tools	["Shell","Docker","Python","Filesystem"]
compatibility	Requires the repo Python environment, Docker Compose, endpoint URLs for shared dependencies, optional Brev CLI access for self-hosted dependency nodes, and provider credentials in the repo-root .env.

name	deploy-collection
description	Deploy the full Content Agents package with a provider-neutral, endpoint-driven, multi-instance strategy. Use when the user asks to deploy all content agents, deploy material/physics/texture together, configure shared OVRTX rendering, choose VLM/LLM/image-gen/embedding endpoints, test the full package, or use Brev as an optional self-hosted dependency provider.
version	0.1.0
author	NVIDIA Content Agents
tags	["content-agents","collection","deployment","brev"]
tools	["Shell","Docker","Python","Filesystem"]
compatibility	Requires the repo Python environment, Docker Compose, endpoint URLs for shared dependencies, optional Brev CLI access for self-hosted dependency nodes, and provider credentials in the repo-root .env.

deploy-collection

설치 방법

소스 파일 검토

Deploy Content Agents Collection

When to Use

Deploy Content Agents Collection

When to Use

Limitations

Prerequisites

Core Model

Instructions

When To Read References

Existing Skills To Reuse

Validation

Output Format

Troubleshooting

deploy-collection

소스 정보

설치 방법

소스 파일 검토

이 저장소의 다른 Skills

이 저장소의 다른 Skills

Deploy Content Agents Collection

When to Use

Deploy Content Agents Collection

When to Use

Limitations

Prerequisites

Core Model

Instructions

When To Read References

Existing Skills To Reuse

Validation

Output Format

Troubleshooting